Supplementary Table 3 Morphological attributes of greenspace and adjacent reference built-up land. NDVI: normalized difference of vegetation index; IMP: impervious surface fraction; SVF: sky view factor. Values in parentheses are for built-up reference.

City	ID	Type	NDVI	IMP (%)	Urban SVF	Greenspace image	Urban image
San Lorenzo, USA	1	Grass	0.32 (0.09)	19 (83)	0.7 - 1
San Lorenzo, USA	2	Tree-grass Mixture	0.37 (0.11)	10 (96)	0.7 - 1
San Lorenzo, USA	3	Grass	0.26 (0.11)	42 (96)	0.7 - 1
Los Angeles, USA	4	Grass	0.35 (0.09)	9 (86)	0.7 - 1
Los Angeles, USA	5	Grass	0.37 (0.12)	12 (89)	0.7 - 1
Los Angeles, USA	6	Grass	0.4 (0.12)	19 (89)	0.7 - 1
Los Angeles, USA	7	Grass	0.35 (0.12)	23 (86)	0.7 - 1
Los Angeles, USA	8	Grass	0.34 (0.10)	17 (89)	0.7 - 1
Los Angeles, USA	9	Grass	0.44 (0.08)	19 (99)	0.7 - 1
Los Angeles, USA	10	Grass	0.33 (0.09)	34 (99)	0.2 – 0.6
San Francisco, USA	11	Tree Canopy	0.38 (0.10)	10 (92)	0.2 – 0.6
San Francisco, USA	12	Grass	0.36 (0.10)	12 (92)	0.2 – 0.6
San Francisco, USA	13	Tree Canopy	0.35 (0.12)	8 (92)	0.2 – 0.6
San Francisco, USA	14	Tree-grass Mixture	0.2 (0.13)	21 (99)	0.7 - 1
Provo, USA	15	Grass	0.44 (0.15)	37 (96)	0.2 – 0.6
Provo, USA	16	Grass	0.49 (0.15)	27 (96)	0.2 – 0.6
Provo, USA	17	Grass	0.6 (0.16)	18 (96)	0.2 – 0.6
Logan, USA	18	Tree-grass Mixture	0.62 (0.19)	10 (98)	0.7 - 1
Logan, USA	19	Tree-grass Mixture	0.64 (0.15)	10 (92)	0.2 – 0.6
Logan, USA	20	Crop	0.51 (0.24)	6 (73)	0.6 – 0.9
Logan, USA	21	Tree Canopy	0.51 (0.14)	25 (100)	0.7 - 1
Logan, USA	22	Grass	0.41 (0.17)	21 (99)	0.7 - 1
Logan, USA	23	Grass	0.36 (0.17)	9 (99)	0.7 - 1
Logan, USA	24	Crop	0.5 (0.14)	12 (98)	0.7 - 1
Logan, USA	25	Crop	0.58 (0.16)	6 (99)	0.7 - 1
Logan, USA	26	Grass	0.59 (0.15)	14 (73)	0.7 - 1
Logan, USA	27	Tree-grass Mixture	0.6 (0.14)	31 (98)	0.7 - 1
Logan, USA	28	Crop	0.37 (0.13)	10 (98)	0.7 - 1
London, UK	29	Tree-grass Mixture	0.25 (0.16)	22 (96)	0.6 - 0.9
London, UK	30	Tree-grass Mixture	0.39 (0.04)	11 (100)	0.3 - 0.6
London, UK	31	Tree-grass Mixture	0.39 (0.08)	14 (99)	0.3 - 0.6
North Platte, USA	32	Crop	0.57 (0.16)	3 (91)	0.7 - 1
North Platte, USA	33	Crop	0.59 (0.34)	1 (57)	0.7 - 1
North Platte, USA	34	Grass	0.6 (0.25)	1 (60)	0.7 - 1
North Platte, USA	35	Crop	0.63 (0.31)	2 (60)	0.7 - 1
North Platte, USA	36	Tree-grass Mixture	0.6 (0.27)	3 (60)	0.7 - 1
North Platte, USA	37	Tree-grass Mixture	0.54 (0.27)	9 (60)	0.7 - 1
Anchorage, USA	38	Tree-grass Mixture	0.47 (0.17)	15 (66)	0.7 - 1
Anchorage, USA	39	Tree Canopy	0.26 (0.14)	9 (87)	0.7 - 1
Anchorage, USA	40	Tree Canopy	0.73 (0.13)	2 (78)	0.7 - 1
Anchorage, USA	41	Tree Canopy	0.44 (0.15)	14 (80)	0.7 - 1
Anchorage, USA	42	Tree-grass Mixture	0.58 (0.16)	9 (66)	0.7 - 1
Anchorage, USA	43	Tree-grass Mixture	0.41 (0.16)	9 (66)	0.7 - 1
Anchorage, USA	44	Tree Canopy	0.57 (0.13)	3 (78)	0.7 - 1
Anchorage, USA	45	Tree Canopy	0.5 (0.14)	12 (66)	0.7 - 1
Anchorage, USA	46	Tree Canopy	0.51 (0.13)	6 (78)	0.7 - 1
Washington DC, USA	47	Tree Canopy	0.74 (0.26)	5 (90)	0.5 - 0.8
Washington DC, USA	48	Tree Canopy	0.5 (0.23)	24 (90)	0.5 - 0.8
Washington DC, USA	49	Tree-grass Mixture	0.37 (0.23)	56 (90)	0.5 - 0.8
Washington DC, USA	50	Tree-grass Mixture	0.37 (0.23)	30 (90)	0.5 - 0.8
Washington DC, USA	51	Tree-grass Mixture	0.56 (0.24)	18 (90)	0.5 - 0.8
Washington DC, USA	52	Grass	0.5 (0.23)	20 (90)	0.5 - 0.8
Washington DC, USA	53	Tree Canopy	0.66 (0.23)	6 (90)	0.5 - 0.8
New Haven, USA	54	Tree Canopy	0.77 (0.34)	6 (93)	0.5 - 0.8
New Haven, USA	55	Tree Canopy	0.73 (0.34)	9 (94)	0.3 - 0.6
New Haven, USA	56	Tree-grass Mixture	0.56 (0.34)	24 (93)	0.5 - 0.8
New Haven, USA	57	Tree Canopy	0.54 (0.40)	7 (67)	0.6 - 0.9
New Haven, USA	58	Tree-grass Mixture	0.45 (0.28)	35 (93)	0.6 - 0.9
New Haven, USA	59	Grass	0.47 (0.25)	31 (93)	0.6 - 0.9
New Haven, USA	60	Tree Canopy	0.55 (0.24)	15 (93)	0.6 - 0.9
New Haven, USA	61	Tree Canopy	0.67 (0.41)	10 (67)	0.6 - 0.9
New Haven, USA	62	Tree Canopy	0.81 (0.24)	4 (85)	0.7 - 1
New Haven, USA	63	Tree-grass Mixture	0.62 (0.25)	14 (93)	0.6 - 0.9
New Haven, USA	64	Tree Canopy	0.85 (0.25)	3 (93)	0.6 - 0.9
New Haven, USA	65	Grass	0.42 (0.25)	22 (86)	0.7 - 1
New Haven, USA	66	Tree-grass Mixture	0.62 (0.34)	4 (93)	0.5 - 0.8
North Branford, USA	67	Grass	0.46 (0.16)	0 (84)	0.5 - 0.8
North Branford, USA	68	Tree Canopy	0.57 (0.16)	2 (84)	0.5 - 0.8
North Branford, USA	69	Crop	0.47 (0.16)	3 (84)	0.5 - 0.8
North Branford, USA	70	Tree Canopy	0.45 (0.16)	10 (84)	0.5 - 0.8
North Branford, USA	71	Tree-grass Mixture	0.48 (0.16)	10 (84)	0.5 - 0.8
Nanjing, China	72	Tree-grass Mixture	0.57 (0.35)	46 (77)	0.5 - 0.7
Nanjing, China	73	Crop	0.35 (0.33)	21 (88)	0.5 - 0.7
Nanjing, China	74	Tree Canopy	0.49 (0.23)	44 (93)	0.2 - 0.4
Nanjing, China	75	Tree-grass Mixture	0.53 (0.33)	39 (88)	0.5 - 0.7
Nanjing, China	76	Tree Canopy	0.74 (0.45)	4 (60)	0.5 - 0.8
Nanjing, China	77	Grass	0.51 (0.33)	38 (88)	0.5 - 0.7
Nanjing, China	78	Crop	0.46 (0.33)	36 (88)	0.5 - 0.7
Nanjing, China	79	Tree Canopy	0.62 (0.33)	16 (88)	0.5 - 0.7
Hangzhou, China	80	Tree Canopy	0.5 (0.26)	4 (57)	0.7 - 1
Hangzhou, China	81	Tree Canopy	0.40 (0.22)	4 (57)	0.7 - 1
Hangzhou, China	82	Crop	0.57 (0.30)	7 (57)	0.7 - 1
Hangzhou, China	83	Crop	0.58 (0.30)	15 (57)	0.7 - 1
Hangzhou, China	84	Crop	0.56 (0.30)	13 (57)	0.7 - 1
Hangzhou, China	85	Crop	0.46 (0.17)	29 (82)	0.5 - 0.7
Hangzhou, China	86	Tree Canopy	0.68 (0.27)	6 (81)	0.2 - 0.4
Hangzhou, China	87	Crop	0.35 (0.24)	12 (85)	0.5 - 0.8
Hangzhou, China	88	Tree Canopy	0.5 (0.24)	6 (85)	0.5 - 0.8
Hangzhou, China	89	Grass	0.4 (0.18)	35 (82)	0.5 - 0.7
Hangzhou, China	90	Grass	0.35 (0.20)	27 (81)	0.2 - 0.4
Hangzhou, China	91	Grass	0.41 (0.18)	45 (81)	0.2 - 0.4
Hangzhou, China	92	Tree Canopy	0.40 (0.19)	38 (83)	0.5 - 0.7
Hangzhou, China	93	Tree Canopy	0.41 (0.11)	42 (92)	0.3 - 0.6
Hangzhou, China	94	Grass	0.30 (0.19)	39 (94)	0.7 - 1
Hangzhou, China	95	Crop	0.32 (0.20)	31 (81)	0.2 - 0.4
Hangzhou, China	96	Grass	0.40 (0.19)	28 (81)	0.2 - 0.4
Hangzhou, China	97	Tree-grass Mixture	0.39 (0.19)	30 (81)	0.2 - 0.4
Hangzhou, China	98	Crop	0.37 (0.20)	31 (95)	0.5 - 0.7
Hong Kong, China	99	Tree Canopy	0.38 (0.08)	53 (99)	0.2 - 0.4
Hong Kong, China	100	Tree Canopy	0.24 (0.07)	55 (93)	0.2 - 0.4
Hong Kong, China	101	Tree Canopy	0.29 (0.08)	25 (99)	0.2 - 0.4
Hong Kong, China	102	Tree-grass Mixture	0.37 (0.06)	46 (99)	0.2 - 0.4
Guangzhou, China	103	Tree Canopy	0.57 (0.30)	29 (72)	0.5 - 0.7
Guangzhou, China	104	Tree Canopy	0.49 (0.40)	18 (71)	0.5 - 0.7
Guangzhou, China	105	Tree Canopy	0.40 (0.13)	16 (100)	0.6 - 0.9
Guangzhou, China	106	Tree Canopy	0.35 (0.14)	38 (100)	0.6 - 0.9
Guangzhou, China	107	Tree Canopy	0.32 (0.13)	35 (100)	0.6 - 0.9
Guangzhou, China	108	Tree Canopy	0.34 (0.16)	27 (99)	0.6 - 0.9
Guangzhou, China	109	Tree-grass Mixture	0.42 (0.29)	50 (90)	0.5 - 0.7
Guangzhou, China	110	Tree Canopy	0.47 (0.18)	19 (99)	0.6 - 0.9
Guangzhou, China	111	Crop	0.37 (0.29)	34 (83)	0.2 - 0.4
Guangzhou, China	112	Tree Canopy	0.56 (0.29)	19 (83)	0.2 - 0.4
Guangzhou, China	113	Tree-grass Mixture	0.34 (0.29)	25 (83)	0.2 - 0.4
Guangzhou, China	114	Tree-grass Mixture	0.47 (0.29)	8 (83)	0.2 - 0.4

Vegetation type is based on visual inspection of Google Earth images. NDVI is warm season value based on Sentinel-2 satellite observations. Cropland was identified using FROM-GLC10 global landcover data 2017 (https://data-starcloud.pcl.ac.cn/resource/1). IMP is based on ESA Worldwide Land Cover Mapping 2021 (https://esa-worldcover.org/en). SVF is the value of the dominant local climate zone (LCZ) of the built-up neighborhood. LCZ classification data: https://www.wudapt.org. SVF values associated with LCZs from Stewart (2012, ref⁴⁶).